ECE Seminar: Closing the Loop: From Data to Actions for Intelligent Physical Systems

Time: Thursday, March 27, 2025 - 3:00pm - 4:00pm
Type: Seminar Series
Presenter: Na Li “Lina” Harvard University
Room/Office:
Location:
DL 514 or Zoom
10 Hillhouse Avenue
New Haven, CT 06511
United States

Closing the Loop: From Data to Actions for Intelligent Physical Systems

Na Li “Lina” Harvard University

Th. March 27 at 3:00pm

DL514 or Zoom (https://yale.zoom.us/j/98165195776)

Hosted by: Professor Steve Morse

Abstract:

The explosive growth of machine learning and data-driven methodologies have revolutionized numerous fields. Yet, translating these successes to the domain of dynamical physical systems remains a significant challenge, hindered by the complex and often unpredictable nature of such environments. Closing the loop from data to actions in these systems faces many difficulties, stemming from the need for sample efficiency and computational feasibility amidst intricate dynamics, along with many other requirements such as verifiability, robustness, and safety. In this talk, we bridge this gap by introducing innovative approaches that harness representation-based methods, domain knowledge, and the physical structures of systems. We present a comprehensive framework that integrates these components to develop reinforcement learning and control strategies that are not only tailored for the complexities of physical systems but also achieve efficiency, safety, and robustness with provable performance.

Bio:

Na Li is a Winokur Family Professor of Electrical Engineering and Applied Mathematics at Harvard University and a visiting researcher in Mitsubishi Electric Research laboratories (MERL).  She received her Bachelor's degree in Mathematics from Zhejiang University in 2007 and Ph.D. degree in Control and Dynamical systems from California Institute of Technology in 2013. She was a postdoctoral associate at the Massachusetts Institute of Technology 2013-2014.  She has held a variety of short-term visiting appointments including the Simons Institute for the Theory of Computing, MIT, and Google Brain. Her research lies in the control, learning, and optimization of networked systems, including theory development, algorithm design, and applications to real-world cyber-physical societal system.  She has been an associate editor for IEEE Transactions on Automatic Control, Systems & Control Letters, IEEE Control Systems Letters, and served on the organizing committee for a few conferences.  She received the NSF career award, AFOSR Young Investigator Award, ONR Young Investigator Award,  Donald P. Eckman Award, McDonald Mentoring Award, IFAC Distinguished Lecture, IFAC Manfred Thoma Medal, Ruberti Young Researcher Prize, along with other awards.